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STAT 406 Project: Full Factorial Design. Analysis of key players and their performance in pre-covid arenas versus in the bubble.

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NBA: Built for the Bubble

Fall 2020

  • Isaac Ke, Johnathan Lo, Michael Lee, and Tianyi Jiang

  • Full Factorial Design

  • Analyses of 6 key players and their performance in pre-covid arenas versus in the bubble:

    • Paul George (suspected UNDER-performer)
    • Pascal Siakam (suspected UNDER-performer)
    • Giannis Antetokounmpo (suspected UNDER-performer)
    • Jamal Murray (suspected OVER-performer)
    • Donovan Mitchell (suspected OVER-performer)
    • Jimmy Butler (suspected OVER-performer)
  • Data from Basketball-Reference

  • Analysis done in JMP Pro 15

  • A full report containing an introduction to the problem, explanation of methods, model results, conclusions, and discussion can be found here.


Introduction & Motivation

The COVID-19 pandemic brought with it many challenges in the sports world. Sports have always revolved around the fans, but unfortunately, events involving fans often result in “super-spreader” events that worsen the pandemic. The National Basketball Association (NBA) was one of many sport leagues that had their season interrupted by the pandemic. Their solution was to implement a contained, quarantined environment in Orlando, Florida called the “Bubble”, where game-play could continue under strict precautionary procedures.

In this investigation, we were interested in comparing NBA player performance inside and outside the Bubble. The Bubble provided a contrast to the usual regime of home and away games. Since all teams competed on the same court without fan presence, it is conceivable that the effect of home and away games on player performance might have changed in the Bubble. For a few players, this perceived difference between their normal play and their Bubble play seemed especially pronounced. These differences were exploited by the media and developed into influential narratives that shaped the 2020 NBA postseason. As such, we were particularly interested in assessing whether the Bubble phenom was real for these specific players, and whether or not these effects conformed to the media narrative.

The primary objective of our analyses was to identify the effects of home and Bubble games on player performance. The Bubble provided an unprecedented opportunity to examine the impact of fans and packed arenas on professional sport outcomes by providing a controlled, identical setting for competition. Using a full factorial design, we tested the significance and magnitude of playing at home, playing in the Bubble, and their interaction.

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STAT 406 Project: Full Factorial Design. Analysis of key players and their performance in pre-covid arenas versus in the bubble.

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